Transforming Data-Centric XML Into Relational Databases Using Node-Based And Path-Based Approaches

Citation

Mohd Tarmizi Song, Emyliana (2020) Transforming Data-Centric XML Into Relational Databases Using Node-Based And Path-Based Approaches. Masters thesis, Multimedia University.

Full text not available from this repository.

Abstract

eXtensible Markup Language (XML) has emerged as the standard for information representation over the Internet. However, most enterprises today have long secured the use of relational databases. Thus, it is crucial to map XML data into relational data to provide seamless integration between these database infrastructures. Many mapping techniques have been proposed, yet, none has provided a unified view on these techniques. Ultimately, understanding how these techniques work is important especially if one needs to decide which technique to adopt in their organization. Three objectives were set for this research. Firstly, is to study existing mapping approaches on model-based mapping scheme. Literature reviews on many existing approaches has been done to identify the advantages and shortcomings of each approach. Secondly, is to propose an efficient model-based mapping scheme to bridge XML technologies and relational databases. Lastly, is to evaluate the performance of the proposed mapping scheme as compared to existing approaches. Performance of the algorithms will be measured by using the time taken to map the data from XML into RDB and the storage size that used to store the data.

Item Type: Thesis (Masters)
Additional Information: Call No.: QA76.76.H94 E49 2020
Uncontrolled Keywords: XML (Document markup language)
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 17 Sep 2020 02:57
Last Modified: 17 Sep 2020 02:57
URII: http://shdl.mmu.edu.my/id/eprint/7717

Downloads

Downloads per month over past year

View ItemEdit (login required)